A novel approach of gait recognition through fusion with footstep information

This paper is focused on two biometric modes which are very linked together: gait and footstep biometrics. Footstep recognition is a relatively new biometric based on signals extracted from floor sensors, while gait has been more researched and it is based on video sequences of people walking. This paper reports a directly comparative assessment of both biometrics using the same database (SFootBD) and experimental protocols. A fusion of the two modes leads to an enhanced gait recognition performance, as the information from both modes comes from different capturing devices and is not very correlated. This fusion could find application in indoor scenarios where a gait recognition system is present, such as in security access (e.g. security gate at airports) or smart homes. Gait and footstep systems achieve results of 8.4% and 10.7% EER respectively, which can be significantly improved to 4.8% EER with their fusion at the score level into a walking biometric.